What is meant by backtracking in the data structure?/What is backtracking in the data structure?

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Hello friends, In this, this blog post(What is backtracking in a data structure) I am going to let you know about one more interesting technique named backtracking to solve the problem in the data structure. Which most of you would have read during your study period or engineering.

Inside this blog(What is backtracking in a data structure), we will cover What is meant by backtracking in the data structure. What is meant by backtracking? Which data structure is used for backtracking? What is the difference between recursion and backtracking?

What is the difference between recursion and backtracking?

In recursion, a function calls itself until it reaches the base case, and in backtracking, we use recursion until we find the best solution. So recursion is a process to reach the base case and backtracking is the process to get the best solution.

Backtracking is very helpful in solving problems where we have a set of n number of solutions or in other words, have multiple solutions for solving one particular problem,…

… and then we need to find out the optimal solution for solving that problem by satisfying some constraints too which are part of this problem.

So ultimately under a fixed boundary or predefined constraints, we need to find the best or optimal solution for the particular problem out of all possible solutions to that problem.

In many applications of the backtracking method, the desired solution is expressible as an n-tuple(x1, x2, ………Xn), where Xi is chosen from some finite set of Si.

Generally, the problem to be solved calls for finding one vector that maximizes satisfies, or minimizes a certain function P(x1, x2,…..Xn). Sometimes it seeks all vectors that satisfy P.

Many of the problems we solve using backtracking require that all the solutions satisfy a complex set of constraints. these constraints are divided into two categories for any problem. They are listed below.

Explicit Constraints:

Explicit constraints are rules that restrict each Xi to take on values only from a given set

Some examples that are common for explicit constraints are

Xi>=0 or Si ={all non negative real numbers}
Xi=0 or 1 or Si ={0, 1}
Li<=Xi<=Ui or Si={a:Li<=a<=Ui}

The explicit constraints depend on the particular instance of a problem being solved. All tuples that satisfy the explicit constraints define a possible solution space for I

Implicit Constraints:

Implicit constraints are rules that determine which of the tuples in the solution space of I satisfy the criterion function. Hence implicit constraints give how Xi must relate to each other.

An example that can be solved by the use of the backtracking technique is listed below:

Sorting the array of integers in a {1:n}
8 -Queen problem
4- Queens problem
A sum of subsets problem.

You can also go through a few more amazing blog links below related to Data Structure:

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What is compaction in memory management…
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Dynamic Memory Management…
Josephus problem & Circular linked list…
What is a circular linked list…
What are the linked lists in the data structure and their types…
What is the priority queue with an example…
the difference between stack and queue…
What is meant by backtracking in the data structure…

Conclusion:

In this blog post(What is backtracking in a data structure), we have explored What is meant by backtracking in the data structure. What is meant by backtracking? Which data structure is used for backtracking? What is the difference between recursion and backtracking? Backtracking, Backtracking algorithm explained, Backtracking problems.

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